Evidence map›Paper›PMID 34963690›Full record

ArticleScientific reports2021

Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea.

Sungchan Kim, Minseok Kim, Sunmi Lee, Young Ju Lee

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Trends of new diagnosis and treatment initiation of hypertension during the COVID-19 pandemic in Korea.Hypertension research : official journal of the Japanese Society of Hypertension · 2026
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  7. A mobility-adjusted framework for regional RBMC infectious diseases · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sungchan KimDepartment of Applied Mathematics, Kyung Hee University, Yongin, Republic of Korea.
Minseok KimDepartment of Applied Mathematics, Kyung Hee University, Yongin, Republic of Korea.
Sunmi LeeDepartment of Applied Mathematics, Kyung Hee University, Yongin, Republic of Korea. sunmilee@khu.ac.kr.
Young Ju LeeDepartment of Mathematics, Texas State University, San Marcos, TX, USA. yjlee@txstate.edu.

Funding

Brain Pool Program through 653 the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT 654 NRF2020H1D3A2A01041079Samsung Science and Technology Foundation SSTF-BA2002-02
6 · The paper itself

Abstract

A novel severe acute respiratory syndrome coronavirus 2 emerged in December 2019, and it took only a few months for WHO to declare COVID-19 as a pandemic in March 2020. It is very challenging to discover complex spatial-temporal transmission mechanisms. However, it is crucial to capture essential features of regional-temporal patterns of COVID-19 to implement prompt and effective prevention or mitigation interventions. In this work, we develop a novel framework of compatible window-wise dynamic mode decomposition (CwDMD) for nonlinear infectious disease dynamics. The compatible window is a selected representative subdomain of time series data, in which compatibility between spatial and temporal resolutions is established so that DMD can provide meaningful data analysis. A total of four compatible windows have been selected from COVID-19 time-series data from January 20, 2020, to May 10, 2021, in South Korea. The spatiotemporal patterns of these four windows are then analyzed. Several hot and cold spots were identified, their spatial-temporal relationships, and some hidden regional patterns were discovered. Our analysis reveals that the first wave was contained in the Daegu and Gyeongbuk areas, but it spread rapidly to the whole of South Korea after the second wave. Later on, the spatial distribution is seen to become more homogeneous after the third wave. Our analysis also identifies that some patterns are not related to regional relevance. These findings have then been analyzed and associated with the inter-regional and local characteristics of South Korea. Thus, the present study is expected to provide public health officials helpful insights for future regional-temporal specific mitigation plans.

Indexed as

AlgorithmsCOVID-19HumansRepublic of KoreaSARS-CoV-2Spatio-Temporal AnalysisTime Factors

Identifiers

PMID34963690
PMCPMC8714822

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.